Change to USS rules causes wealth transfers

Updated on 24 April 2016

The Universities Superannuation Scheme’s (USS), one of the three largest UK pension schemes alongside the pension schemes of BT and Lloyds, went ahead with its proposed changes to employees’ pensions and cut expected pensions by 25%. Most of the USS’ current members had their pension linked to their final salary upon retiring, which has been replaced by an inflation indexing rule from 1 April 2016. The new scheme ignores career progression and other salary increases. This will lead to substantial wealth transfers from members of the final salary section to other USS members. Under the new rules, the option for final-salary members to receive a pension based on a future pensionable salary has been removed retroactively, which reduces the value of those members’ accrued benefits. Continue reading

Liquidity, Technological Opportunities, and the Stage Distribution of Venture Capital Investments

Financial Management, Volume 43, Issue 2, pages 291–325, Summer 2014 (Open Access).

with Andrea Mina

Abstract: This paper explores the determinants of the stage distribution of European venture capital investments from 1990 to 2011. Consistent with liquidity risk theory, we find that the likelihood of investing in earlier stages increases relative to all private equity investments during liquidity crisis years. While liquidity is the main driver of acquisition investments and, to some extent, of expansion financings, technological opportunities are overall the main driver of early and late stage venture capital investments. In contrast to the dotcom crash, the recent financial crisis negatively affected the relative likelihood of expansion investments, but not of early and late stage investments.

Dynamic financial constraints and innovation: Evidence from the UK innovation surveys

with Andrea Mina

Abstract: Does innovation cause financial constraints? And how do financial constraints affect firm innovation activities? In this paper we address the challenge of separating bi-directional causal effects in the relationship between innovation and financial constraints. Using the longest panel that can to date be derived from the UK Innovation Surveys, we construct novel simultaneous equations models with indicators for innovation, including expenditures for internal and external R&D, product innovation and process innovation, and for perceived financial constraints. The empirical analysis reveals a persistent impact of innovation inputs, and also outputs, on the likelihood that firms experience financial constraints. This effect is strongest for the observation of an R&D programme and relatively weak for R&D expenditures. Innovation outputs in the form of products new to the market seem to cause financial constraints – an important finding from a policy perspective. The reverse effect of financial constraints on innovation appears negligible.

Available here (latest version: September 2013).

We won the best paper award at this year’s CONCORDi conference on “Financing R&D and innovation for corporate growth in the EU: Strategies, drivers and barriers” for Andrea Mina’s and my paper on “Dynamic financial constraints and innovation: Evidence from the UK innovation surveys”. Thanks to the conference team for an exceptionally productive time in Seville and the conference participants for their encouraging and constructive comments!

Signalling, absorptive capacity and the geographic patterns of academic knowledge exchange

with Alan Hughes and Michael Kitson

Abstract: In this paper, we investigate the geographic distance in collaborations between academics and external organisations across different knowledge exchange channels. This analysis is based on a unique large sample of UK academics. We ask the following questions. First, how far does academic knowledge, explicit or tacit, travel? Second, which academics engage in which collaborations? Third, how does the type of knowledge transfer moderate the effect of individual and department-level absorptive capacity on geographic distance? Fourth, which quality signals or market characteristics affect the formation and distance of knowledge exchange collaborations? We find that the capacity to identify and absorb knowledge helps to explain the geographic distance in collaborations. In part
icular, age, academic seniority and specific types of professional experience are positively related to geographic distance in transfers of tacit knowledge. Strong common effects of seniority and research quality across channels suggest that the ability to signal the availability and quality of knowledge as a tradable asset dominates the explanatory power of absorptive capacity. The effects of support at the university level are weak, while regional concentration of business R&D expenditures increases collaboration distance.

Available here.

Latest version: March 2013

An Improved Test for Earnings Management Using Kernel Density Estimation

European Accounting Review, Volume 23, Issue 4, 2014, pp. 559-591.

Abstract: The methods proposed by Burgstahler and Dichev (1997) and Bollen and Pool (2009) to test for earnings management have been used extensively in the literature. This paper proposes a more general test procedure based on kernel density estimation using a kernel bandwidth selected by a bootstrap test. Its main advantage over prior methods is the construction of a kernel density estimate that cannot be globally distinguished from the empirical distribution, which greatly reduces an upward bias in test statistics found in earlier results. It limits the researcher’s degrees of freedom and offers a simple procedure to find and test a local discontinuity. I apply the bootstrap density estimation to earnings, earnings changes, and earnings forecast errors in U.S. firms over the period 1976-2010. Results confirm earlier findings of discontinuities in the whole sample of earnings and earnings changes, but not in all subsamples. There is a large drop in loss aversion after 2002, which cannot be detected in earnings changes. Discontinuities in analysts’ forecast errors found by earlier research are more likely to be caused by rounding errors than by earnings management.

Published in the European Accounting Review. If you cannot access the article, please let me know.
A working paper version is available at SSRN (latest version: August 2013).

Short presentation of method and key findings

The main motivation why we need to move from Burgstahler and Dichev’s method of testing discontinuities to a more refined approach is presented in this document: Earnings_management_KDE.pdf.

Estimation algorithms

The current version of the test procedure is implemented in R and Stata. The Stata code is available from the journal as a supplemental file, the R version can be downloaded here. The R version is about two or three times faster than the Stata one. If you are investigating earnings management or plan to implement the algorithm, please get in touch. Please also let me know if you find any errors or if you develop the algorithm further.

Interpretation of failures to converge (AKA: commonly found problems)

If the data generating process for the data to be tested for a discontinuity does not produce a distribution that has a step discontinuity but some other kind of discontinuity, the algorithm may fail to converge. The algorithm typically fails to converge for “distributions” like Durtschi & Easton’s (2005) unscaled EPS, in which individual observations are not drawn from the same underlying distribution. In the case of earnings per share, this produces a spike at zero (and an asymptotic discontinuity in theory), not a step discontinuity as in typical earnings management. This behaviour of the algorithm is also discussed in the paper. Non-convergence may thus be interpreted as a signal that the distribution tested is degenerate and does not have a step discontinuity.

The same non-convergence behaviour can be observed, if for some reason a large point mass exists somewhere in the region to be tested (typically anywhere on the real line). For example, numerical values as indicators for missing values or a large number of zeros caused by rounding or other reasons may lead to non-convergence. This is again caused by the underlying distribution not having a step discontinuity.

Last updated: May 2, 2015.